A wide range of systems have been proposed and are currently in use for producing discrete pixel images. In such systems, data is gathered representative of characteristics of a large number of picture elements or pixels arranged in an array or matrix. For example, in digital radiography systems, signals are produced which are representative of a level or intensity of radiation received within each pixel region during an exposure. The signals are processed and filtered to provide consistent and meaningful information over the matrix of pixels. Following such processing, the data is used to reconstruct a useful composite image made up of the pixels. The particular filtering and processing of the signals may be adapted to various modalities and features of interest, so as to provide a user with meaningful information in their reconstructed image. In many medical applications, an attending physician or radiologist will consult the composite image for identification of internal features within a subject as defined by edges, textural regions, contrasted regions, and so forth.
Algorithms have been developed for digitally processing discrete pixel image data to enhance diagnostic portions of the image while suppressing noise. For example, in one known method pixel data is filtered through progressive low pass filtering steps. The original image data is thus decomposed into a sequence of images having known frequency bands. Gain values are applied to the resulting decomposed images for enhancement of image features, such as edges. Additional filtering, contrast equalization, and gradation steps may be employed for further enhancement of the image.
While such techniques provide useful mechanisms for certain types of image enhancement, they are not without drawbacks. For example, gains applied to decomposed images can result in inadvertent enhancement of noise present in the discrete pixel data. Such noise, when enhanced, renders the reconstructed image difficult to interpret, and may produce visual artifacts which reduce the utility of the reconstructed image, such as by rendering features of interest difficult to discern or to distinguish from non-relevant information.
There is a need, therefore, for an improved technique for discrete pixel image enhancement. In particular, there is a need for a technique which is capable of enhancing features of interest in such images, such as edges of structures, without enhancement of noise or other artifacts. There is also a particular need for an image enhancement technique which can be employed in existing systems, and which can be adjusted by users for various situations, depending upon the type of subject being imaged, the features of interest, and so forth.